The main objective of this study is to provide better means of analysis and interpretation of cohort studies, for example, in epidemiology the analysis of the mortality experience of reconstructed cohorts of industrial workers. Problems with current methods, such as those producing standardized mortality ratios, include inadequacy of available comparison populations and limitations in interpretation. Of interest here is survivorship analysis of heterogeneous cohorts, for example, cohort mortality in environmental studies of the impact of pollution episodes or in occupational settings, where those individuals at the outset differ with regard to age, are not all of the same race or sex, and may have varying times of exposure, all these factors being related to survivorship. These are traits which are common in observational studies. This leads to study of survivorship methods with covariables, which have apparently not been applied to cohort mortality studies in the past. Use of these methods will allow interpretations of results reflecting various assessments of individual risks. Such phenomena as the healthy worker effect may become more clearly understood by study of the change in survival probabilities with time. Applicability of these methods is not limited to mortality studies alone, but may be employed for any well-defined health outcome. These methods will also help in providing techniques for design of cohort studies. Currently, the tendency in observational studies is to study as many individuals as possible for as long as possible. The techniques for analysis that are proposed here will provide the basis for decisions to study fewer individuals for possibly a shorter length of time, as well as indicate what information a particular cohort study would be expected to yield before it is executed.